Artificial Intelligence-Based Assessment and Student Performance: The Mediating Role of Digital Competence in the University Context

Abstract

This study investigates the impact of artificial intelligence-based assessment (AIBA) on student performance (SP) in higher education and examines the mediating role of digital competence (DC). Using data collected from 211 students enrolled in Pakistani universities, the study employed structural equation modelling (SEM) to test the hypothesised relationships among AIBA, DC, and SP. The results reveal that AIBA significantly and positively affects student performance, while digital competence serves as a strong mediator in this relationship. Specifically, exposure to AIBA not only enhances learning outcomes through personalised feedback and adaptive assessment but also strengthens students’ digital capabilities, which are increasingly vital in technology-driven educational environments. These findings suggest that the effectiveness of AIBA depends substantially on learners’ digital readiness, highlighting that technology itself is not sufficient to ensure improved academic outcomes unless accompanied by the development of essential digital skills. The study contributes to the growing body of literature by being among the first empirical investigations within the Pakistani higher education context to validate the mediating role of DC between AIBA and SP. The integration of insights from the Technology Acceptance Model (TAM), Self-Determination Theory (SDT), and the Resource-Based View (RBV) further provides a multidimensional understanding of how adoption, motivation, and competence interact to enhance learning performance. The study offers important implications for curriculum designers, policymakers, and educators seeking to integrate AI-based assessment tools effectively while fostering digital competence and promoting sustainable academic excellence in the era of intelligent education.